19th International Conference on Artificial
Intelligence and Law - ICAIL 2023

19th-23rd June 2023

Conference Venue:

University of Minho , Law School, Campus de Gualtar (Building 17), Braga, Portugal

Latest news:

5th June 2023
Regular registration deadline extended to June 9.

12th May 2023:
Programme Page updated.

2nd May 2023:
Registration Page updated.

27th April 2023:
Accepted Papers Page updated.

17th April 2023:
Added Visa Requirements information to the Venue and Getting to ICAIL'2023 page.

14th April 2023:
Doctoral Consortium Submission Deadline extended.

12th April 2023:
Sponsors Page updated.

7th March 2023:
Registration Page updated.

22nd February 2023:
Speakers Info Page updated.

21st February 2023:
Workshops Page updated.

3rd January 2023:
Submission Deadline extended.

1st August 2022:
ICAIL'2023 Conference Web site was launched.

19th ICAIL - International Conference on Artificial Intelligence and Law 2023 (ICAIL 2023).

Since 1987, the International Conference on Artificial Intelligence and Law (ICAIL) has been the foremost international conference addressing research in Artificial Intelligence and Law. It is organized biennially under the auspices of the International Association for Artificial Intelligence and Law (IAAIL), and in cooperation with the Association for the Advancement of Artificial Intelligence (AAAI). The conference proceedings are published by ACM. We invite submissions of papers along a regular and three special tracks, technology demonstrations, as well as proposals for workshops and tutorials.

Organized by


We invite submission of original papers on Artificial Intelligence & Law, covering foundations, methods, tools, systems and applications. Topics may include, but are not limited to, the following:

ICAIL is keen to broaden its scope to include topics of growing importance and to establish links to neighboring disciplines. In addition to the regular paper track, ICAIL 2023 will feature the following special tracks:

(1) a new special cross-disciplinary outreach track on Artificial Intelligence for Empirical Legal Studies. Legal systems have seen an increasing need to leverage data analysis to inform stakeholders, decision makers, and policy actors. This potential comes with a mandate for credible empirical research, as well as constructive communication, across communities at the intersection of law and data-driven disciplines. The empirical legal studies and AI&Law communities stand to benefit from an exchange of ideas and collaborations around concrete legal use cases, technical approaches, and commitment to using data-driven technology for policy and social good. For this track we invite short and long submissions of original papers on topics including, but not limited to:

(2) Innovative applications in AI and Law – Applications that fall within any of the core AI & Law topics. P apers in this track will be subject to the same rigorous reviewing process as regular papers, but the emphasis is less on novel scientific contributions, formal frameworks, or results and more on the innovative and novel application of techniques from AI & Law to real world problems and use cases.

(3) Legal, ethical, fairness, accountability, and transparency aspects of AI applications in legal practice, access to justice, compliance, and public administration – ICAIL is committed to not only further the state of the art in using AI technology in legal practice, but also about the legal and ethical ramifications of such applications. This track is intended to facilitate this discourse through the inclusion of case studies, reports on regulations efforts, lessons learned from experiments, technical contributions about monitoring and facilitating ethical use of AI in relevant areas, and other topical contributions. Papers in this track will be subject to the same rigorous reviewing process as regular papers.

Paper Submission

Papers (up to 10 pages including references for long papers, up to 5 pages including references for short papers) should present contributions from relevant topics. To maintain ICAIL’s relevance in the larger rapidly-moving field at the intersection of law and artificial intelligence, all papers must make clear their relation to legal information, reasoning, or processes as well as relation to prior work and novel scientific contribution, as well as contain a satisfying amount of discussion of their findings.

It is highly recommended for all submissions that code and data be published alongside the papers to facilitate reproducibility. Program committee members will be instructed to take data and code sharing into account in their reviews.

Paper must formatted using the ACM sigconf template (for LaTeX) or the interim template layout.docx (for Word), both at http://www.acm.org/publications/proceedings-template All papers should be converted to PDF prior to electronic submission. Papers that do not adhere to these conditions will be rejected without review.

Submissions should be uploaded in the conference support system Conftool by the submission deadline. For each submission, it should be indicated whether it belongs in the regular track or one of the special tracks (AI&Law for Empirical Legal Studies or Innovative Applications or Ethical and Legal Issues for AI in Legal Practice) using the facility provided by the submission system.

Reviewing will be double blind. Papers submitted for review must not include names and affiliations of the authors and not include an acknowledgments section. Any identifying text in the body of the paper (e.g. citing “our work”) should be removed or rephrased to be non-identifying. These aspects can be added at the camera-ready stage. Therefore, prior to submission of the paper, the authors should first register the paper on the conference support system in order to receive an ID number for the paper. Then, in order to submit the paper, the paper should be revised so that the ID number of the paper replaces the names and affiliations of the authors. The references should include published literature relevant to the paper, including previous works of the authors, though care should be taken in the style of writing in order to preserve anonymity. References to code and data intended to be published alongside the papers are to be phrased such that anonymity is preserved.

Submitted papers may not be published as open access preprints before acceptance notifications have been sent. Papers that have already been published as preprints at the time of submission for review must be flagged as such in the review system and must not reference the preprint in the paper.

Papers submitted not adhering to the page limitation or the anonymity requirements may be rejected without review.


A session will be organized for the demonstration of creative, robust, and practical working applications and tools. Where a demonstration is not connected to a submitted paper, a two-page extended abstract about the system should be submitted for review, via the conference support system and following the instructions on paper submission. Accepted extended abstracts will be published in the conference proceedings. For those demonstrations that are connected to a paper in the main track, no separate statement about the demonstration need be submitted, but the author(s) should send an email to the Program Chair by the demo submission deadline to register their interest in demonstrating their work at this session.

Workshops & Tutorials

ICAIL 2023 will include workshops and tutorials on Monday, June 19 and Friday, June 23. Tutorials should cover a broad topic of relevance to the AI and Law community and should have one or more designated organizers/speakers. Workshops are intended for informal discussion and should have one or more designated organizers as well as an organizing and programming committee. Proposals must contain enough information to permit evaluation on the basis of importance, quality, and community interest. Proposals should be 2 to 4 pages and include at least the following information:

Proposals for workshops and tutorials can be sent by email to the program chair, Matthias Grabmair (matthias.grabmair@tum.de) by the submission deadline.

Doctoral Consortium

ICAIL 2023 will feature a Doctoral Consortium aiming to promote the exchange of ideas from PhD researchers in the area of Artificial Intelligence and Law and to provide them with an opportunity to interact and receive feedback from leading scholars and experts in the field. Details about the consortium’s program and timeline will be published separately from this call for papers.


IAAIL has established three different awards, to be presented at the conference banquet.

Donald H. Berman Award for Best Student Paper

The best student paper award is in memory of Donald H. Berman, a professor of law at Northeastern University, who was a co-founder of the Artificial Intelligence and Law journal. The award consists of a cash gift and free attendance at ICAIL 2023. For a paper to be considered for the award, the student author(s) should be clearly designated as such when the paper is submitted using the facility provided by the submission system, and any non-student co-authors should provide a statement by email to the Program Chair that affirms that the paper is primarily student work.

Carole Hafner Award for Best Paper

The best paper award is given in memory of Carole Hafner, an associate professor of computer science at Northeastern University. She was one of the founders of the ICAIL conference and a co-founding editor of the journal Artificial Intelligence and Law.

Peter Jackson Award for Best Innovative Application Paper

The best innovative application paper award is dedicated to the memory of Peter Jackson, Thomson Reuters’ Chief Research Scientist, who was a strong supporter of the ICAIL conferences and a significant contributor to the development of advanced technologies in AI and Law.

Important Dates


Program Chair

Matthias Grabmair


Conference Local Chair

Francisco Andrade


Conference Local co-Chair

Paulo Novais



Michal Araszkiewicz


AI&Law for Empirical Legal Studies Track Chair

Wolfgang Alschner